How to Guard Against Fraud
9 Ways to Guard Against Fraud
- MasterCard SecureCode and Verified by Visa – These are both 3D Secure protocols that ensure the person attempting the purchase is the owner of the card prior to authorization. Not only do these tools cut down on fraudulent transactions, but they boost consumer confidence that their information is being verified and protected.
- Address Verification Service (AVS) – This is another tool that validates whether the person using the card is the cardholder or not. It works by validating the billing address offered at the time of purchase with the one on file with the issuer during authorization. If the authorization is approved and the AVS response indicates a match, merchants can proceed with the transaction.
- Card Verification Value 2 (CVV2) – This protocol requires the purchaser to enter the three-digit security number printed on the back of a Visa card to verify that the customer making the purchase is in possession of the actual payment card.
- Tokenization – Payment tokenization eliminates the need for merchants to handle or store payment data. Instead, sensitive payment data is replaced with a unique identifier – called a “token” – while the actual payment data is stored in a third-party data center.
- Chargeback alerts – Some third-party solution providers offer chargeback notifications that alert a merchant when a dispute is filed with an issuing bank in the solution provider’s network. This gives the merchant an opportunity to handle the dispute directly with the customer rather than after the entire chargeback process has already occurred. Since chargebacks result in fines and penalties for merchants, it is optimal to address disputes before they turn into chargebacks.
- Device fingerprinting – A device fingerprint is a pattern of online behavior that is identified and attached to a particular device. It can be used to identify devices that have previously been known to commit credit card fraud or online identity theft, making it easy to block purchases and transactions from those devices.
- IP geolocation – IP geolocation can be used to identify anomalies in CNP transactions that may signal fraud. For example, if a billing address and zip code associated with Chicago is entered during the purchase authorization, but the IP address is located in Brazil, this could signal possible fraud. Depending on the type of tool, it may block the transaction altogether or route to a manual review team for further research.
- Behavioral modeling/profiling – Some third-party payment solution providers have created algorithms based on machine learning technology that enables behavioral modeling and profiling. This rules engine can identify and detect potential fraud based on anomalies to establish behavioral patterns associated with payment card data. When “out-of-the-ordinary” patterns or behaviors are identified, the engine alerts the merchant to the inconsistency. From there, merchants can decline the order or submit to manual review for further authentication.
- Big Data – Merchants can tap into multiple data sources in real-time to identify inconsistent or anomalous transaction behavior. Some tools gather social data to detect inconsistencies in location or other identifying information. Some solution providers offer access to negative information databases and behavioral databases, which merchants can use to sniff out suspicious orders and route them for additional verification or review.